You could loop through the list using lapply() or the like. One way would be to subset the data and use . Notation which expands to all variables in the dataset not used elsewhere in the model (ie not the outcomes).
Cheers, Josh On Mar 1, 2012, at 14:29, sajjad R <[email protected]> wrote: > > Dear All, > > I hope to run some simple survival analysis using the cox-proportional hazard > models in R, my command will look like below: > > cox <- summary( coxph( Surv( mortality , TIME ) ~ Independent variables ) ) > > My query is about specifying a range of independnt variables in R, > such that each independent variable is included as the main defining variable > independently of other variables in the variable list. > I have around 10,000 independent variables or groups by which I hope to study > differences in mortality rates over a period of time. > All the 10,000 variables have one thing in common, i.e. their names start > with the same alphabets rs followed by unique 6-8 digit numbers. > > Regards, > > Sajjad > > [[alternative HTML version deleted]] > > ______________________________________________ > [email protected] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
